Brain-Tumor-Classification-with-MRI

VGG16 model-based classification project about brain tumor detection. First, you can check what people are doing on Kaggle using Brain Tumor MRI. Cause I benefited them a lot and it's quite good code parts in it. So here are the links:

https://www.kaggle.com/loaiabdalslam/brain-tumor-mri-classification-vgg16

https://www.kaggle.com/ruslankl/brain-tumor-detection-v1-0-cnn-vgg-16

Me and my friend have done the pre-task given by Teknofest "AI in Healthcare" competition. So it's the classification project and it's only clustered the brain tomography into 'yes' and 'no' folders.

While I was doing that, used a CNN model to classificate the images. And I've create a VGG16 model to do these processes.

And also transfer learning is important and efficient way to creating project in medical image analysis. You can examine what transfer learning is and where it is used from these links:

https://www.kaggle.com/carloalbertobarbano/vgg16-transfer-learning-pytorch

https://www.kaggle.com/hmendonca/mask-rcnn-and-coco-transfer-learning-lb-0-155

https://www.kaggle.com/dansbecker/transfer-learning

As you already know, AlexNet is the best model to do something about BT datas.

In the following days, I'll do classification tasks with other models starting with AlexNet and upload them to my repo.